The RareCyte® platform for next-generation analysis of circulating tumor cells.

Circulating tumor cells (CTCs) can reliably be identified in cancer patients and are associated with clinical outcome. Next-generation "liquid biopsy" technologies will expand CTC diagnostic investigation to include phenotypic characterization and single-cell molecular analysis. We describe here a rare cell analysis platform designed to comprehensively collect and identify CTCs, enable multi-parameter assessment of individual CTCs, and retrieve single cells for molecular analysis. The platform has the following four integrated components: 1) density-based separation of the CTC-containing blood fraction and sample deposition onto microscope slides; 2) automated multiparameter fluorescence staining; 3) image scanning, analysis, and review; and 4) mechanical CTC retrieval. The open platform utilizes six fluorescence channels, of which four channels are used to identify CTC and two channels are available for investigational biomarkers; a prototype assay that allows three investigational biomarker channels has been developed. Single-cell retrieval from fixed slides is compatible with whole genome amplification methods for genomic analysis. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Restricted exchange microenvironments for cell culture.

Metabolite diffusion in tissues produces gradients and heterogeneous microenvironments that are not captured in standard 2D cell culture models. Here we describe restricted exchange environment chambers (REECs) in which diffusive gradients are formed and manipulated on length scales approximating those found in vivo. In REECs, cells are grown in 2D in an asymmetric chamber (<50 µL) formed between a coverglass and a glass bottom cell culture dish separated by a thin (~100 µm) gasket. Diffusive metabolite exchange between the chamber and bulk media occurs through one or more openings micromachined into the coverglass. Cell-generated concentration gradients form radially in REECs with a single round opening (~200 µm diameter). At steady state only cells within several hundred micrometers of the opening experience metabolite concentrations that permit survival which is analogous to diffusive exchange near a capillary in tissue. The chamber dimensions, the openings' shape, size, and number, and the cellular density and metabolic activity define the gradient structure. For example, two parallel slots above confluent cells produce the 1D equivalent of a spheroid. Using REECs, we found that fibroblasts align along the axis of diffusion while MDCK cells do not. MDCK cells do, however, exhibit significant morphological variations along the diffusive gradient.

Multiplexed Exchange-PAINT imaging reveals ligand-dependent EGFR and Met interactions in the plasma membrane.

Signal transduction by receptor tyrosine kinases (RTKs) involves complex ligand- and time-dependent changes in conformation and modification state. High resolution structures are available for individual receptors dimers, but less is known about receptor clusters that form in plasma membranes composed of many different RTKs with the potential to interact. We report the use of multiplexed super-resolution imaging (Exchange-PAINT) followed by mean-shift clustering and random forest analysis to measure the precise distributions of five receptor tyrosine kinases (RTKs) from the ErbB, IGF-1R and Met families in breast cancer cells. We find that these receptors are intermixed nonhomogenously on the plasma membrane. Stimulation by EGF does not appear to induce a change in the density of EGFR in local clusters but instead results in formation of EGFR-Met and EGFR-ErbB3 associations; non-canonical EGFR-Met interactions are implicated in resistance to anti-cancer drugs but have not been previously detected in drug-naïve cells.

RareCyte® CTC Analysis Step 2: Detection of Circulating Tumor Cells by CyteFinder® Automated Scanning and Semiautomated Image Analysis.

The RareCyte CyteFinder instrument is an automated scanner that allows rapid identification of circulating tumor cells (CTCs) on microscope slides prepared by the AccuCyte process (see Chapter 13 ) and stained by immunofluorescence. Here, we present the workflow for CyteFinder scanning, analysis, and CyteMapper scan review which includes CTC confirmation and report generation.

RareCyte® CTC Analysis Step 3: Using the CytePicker® Module for Individual Cell Retrieval and Subsequent Whole Genome Amplification of Circulating Tumor Cells for Genomic Analysis.

The CytePicker module built into the RareCyte CyteFinder instrument allows researchers to easily retrieve individual cells from microscope slides for genomic analyses, including array CGH, targeted sequencing, and next-generation sequencing. Here, we describe the semiautomated retrieval of CTCs from the blood processed by AccuCyte (see Chapter 13) and amplification of genomic DNA so that molecular analysis can be performed.

Evidence for feasibility of fetal trophoblastic cell-based noninvasive prenatal testing.

OBJECTIVE: The goal was to develop methods for detection of chromosomal and subchromosomal abnormalities in fetal cells in the mother's circulation at 10-16 weeks' gestation using analysis by array comparative genomic hybridization (CGH) and/or next-generation sequencing (NGS). METHOD: Nucleated cells from 30 mL of blood collected at 10-16 weeks' gestation were separated from red cells by density fractionation and then immunostained to identify cytokeratin positive and CD45 negative trophoblasts. Individual cells were picked and subjected to whole genome amplification, genotyping, and analysis by array CGH and NGS. RESULTS: Fetal cells were recovered from most samples as documented by Y chromosome PCR, short tandem repeat analysis, array CGH, and NGS including over 30 normal male cells, one 47,XXY cell from an affected fetus, one trisomy 18 cell from an affected fetus, nine cells from a trisomy 21 case, three normal cells and one trisomy 13 cell from a case with confined placental mosaicism, and two chromosome 15 deletion cells from a case known by CVS to have a 2.7 Mb de novo deletion. CONCLUSION: We believe that this is the first report of using array CGH and NGS whole genome sequencing to detect chromosomal abnormalities in fetal trophoblastic cells from maternal blood. © 2016 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.

Spatial information dynamics during early zebrafish development.

During development inherited information directs growth and specifies the complex spatial organization of cells and molecules. Here we show that a new information metric, the k-space information (kSI), captures the growth and emergence of spatial organization in a developing embryo. Using zebrafish as a model, we quantify the rate of development over the first 24h and demonstrate that important developmental landmarks are associated with well-defined transitions in information dynamics. The rate of development during this time is highest immediately before and after gastrulation, as well early in the segmentation period. We also find that the majority of the information arises from spatial correlations on the length scale of 20-80 µm, but there are contributions from many length scales that change over time. A comparison of the information dynamics in the maternal-zygotic one-eyed pinhead mutant, which is defective in mesoderm induction, with the wild-type embryo shows that the information dynamics diverge near the onset of gastrulation. Subsequently the mutant lacks a peak in the information dynamics that appears to be associated with the formation of trunk somites in the wild-type embryo. These findings provide a common and objective basis by which to quantify spatial organization, compare mutants and quantify developmental dynamics. The kSI can also be applied to any form of developmental data of arbitrary dimensions, and it offers a broad conceptual framework with which to organize the large amounts of data emerging from various sources.

Spatial information analysis of chemotactic trajectories.

During bacterial chemotaxis, a cell acquires information about its environment by sampling changes in the local concentration of a chemoattractant, and then uses that information to bias its motion relative to the source of the chemoattractant. The trajectory of a chemotaxing bacteria is thus a spatial manifestation of the information gathered by the cell. Here we show that a recently developed approach for computing spatial information using Fourier coefficient probabilities, the k-space information (kSI), can be used to quantify the information in such trajectories. The kSI is shown to capture expected responses to gradients of a chemoattractant. We then extend the k-space approach by developing an experimental probability distribution (EPD) that is computed from chemotactic trajectories collected under a reference condition. The EPD accounts for connectivity and other constraints that the nature of the trajectories imposes on the k-space computation. The EPD is used to compute the spatial information from any trajectory of interest, relative to the reference condition. The EPD-based spatial information also captures the expected responses to gradients of a chemoattractant, although the results differ in significant ways from the original kSI computation. In addition, the entropy calculated from the EPD provides a useful measure of trajectory space. The methods developed are highly general, and can be applied to a wide range of other trajectory types as well as non-trajectory data.

Computing spatial information from Fourier coefficient distributions.

The spatial relationships between molecules can be quantified in terms of information. In the case of membranes, the spatial organization of molecules in a bilayer is closely related to biophysically and biologically important properties. Here, we present an approach to computing spatial information based on Fourier coefficient distributions. The Fourier transform (FT) of an image contains a complete description of the image, and the values of the FT coefficients are uniquely associated with that image. For an image where the distribution of pixels is uncorrelated, the FT coefficients are normally distributed and uncorrelated. Further, the probability distribution for the FT coefficients of such an image can readily be obtained by Parseval's theorem. We take advantage of these properties to compute the spatial information in an image by determining the probability of each coefficient (both real and imaginary parts) in the FT, then using the Shannon formalism to calculate information. By using the probability distribution obtained from Parseval's theorem, an effective distance from the uncorrelated or most uncertain case is obtained. The resulting quantity is an information computed in k-space (kSI). This approach provides a robust, facile and highly flexible framework for quantifying spatial information in images and other types of data (of arbitrary dimensions). The kSI metric is tested on a 2D Ising model, frequently used as a model for lipid bilayer; and the temperature-dependent phase transition is accurately determined from the spatial information in configurations of the system.

Nanometer-scale embossing of polydimethylsiloxane.

Microstructured polydimethylsiloxane (PDMS) is an important and widely used material in biology and chemistry. Here we report that micrometer- and nanometer-scale features can be introduced into the surface of PDMS in a process that is functionally equivalent to embossing. We show that surface features <50 nm can be replicated onto the surface of previously cured PDMS at room temperature and at low pressure. This type of embossing can be performed on samples in solution. It also allows one template to be used for many different types of microstructures by changing the embossing time or serial embossing at different alignments. The balance between elastic and plastic properties of the PDMS has the effect of high-pass filtering the features that are captured and produces a sample that is suitable for sensitive surface characterization technologies such as atomic force microscopy. These findings extend the applications of PDMS as well as open the possibility for new uses.

Micropatterns of an extracellular matrix protein with defined information content.

One powerful approach to understanding how cells process spatially variant signals is based on using micropatterned substrates to control the distribution of signaling molecules. However, quantifying spatially complex signals requires an appropriate metric. Here we propose that the Shannon information theory formalism provides a robust and useful way to quantify the organization of proteins in micropatterned systems. To demonstrate the use of informational entropy as a metric, we produced patterns of lines of fibronectin with varying information content. Fibroblasts grown on these patterns were sensitive to very small changes in informational entropy (6.6 bits), and the responses depended on the scale of the pattern.

High fidelity functional patterns of an extracellular matrix protein by electron beam-based inactivation.

Controlling the organization of proteins on surfaces provides a powerful biochemical tool for determining how cells interpret the spatial distribution of local signaling molecules. Here, we describe a general high fidelity approach based on electron beam writing to pattern the functional properties of protein-coated surfaces at length scales ranging from tens of nanometers to millimeters. A silicon substrate is first coated with the extracellular matrix protein fibronectin, which is then locally inactivated by exposure to a highly focused electron beam. Biochemical inactivation of the protein is established by the loss of antibody binding to the fibronectin. Functional inactivation is determined by the inability of cells to spread or form focal adhesions on the inactivated substrate, resulting in cell shapes constrained to the pattern, while they do both (and are unconstrained) on the remaining fibronectin. These protein patterns have very high fidelity, and typical patterns agree with the input dimensions of the pattern to within 2%. Further, the feature edges are well defined and approach molecular dimensions in roughness. Inactivation is shown to be dose dependent with observable suppression of the specific binding at 2 microC cm(-2) and complete removal of biochemical activity at approximately 50 microC cm(-2) for 5 keV electrons. The critical dose for inactivation also depends on accelerating voltage, and complete loss of antibody binding was achieved at approximately 4-7 microC cm(-2) for 1 keV electrons, which corresponds to approximately 50-90 electrons per cross-sectional area of a whole fibronectin dimer and ~2-4 electrons per type III fibronectin domain. AFM analysis of the pattern surfaces revealed that electron beam exposure does not remove appreciable amounts of material from the surface, suggesting that the patterning mechanism involves local inactivation rather than the ablation that has been observed in several organic thin film systems.

Electron beam patterning of fibronectin nanodots that support focal adhesion formation.

Nanodots of fibronectin which have radii as small as 100 nm and are biofunctional at the cellular level, can be rapidly fabricated in arbitrary spatial patterns using a technique based on electron beam exposure of a protein monolayer with subsequent backfilling of a second protein species.